Description

Properties

Name — Layer name'' (default) | character vector | string scalar

Layer name, specified as a character vector or a string scalar.
To include a layer in a layer graph, you must specify a nonempty unique layer name. If you train
a series network with the layer and Name is set to '',
then the software automatically assigns a name to the layer at training time.

Data Types: char | string

NumInputs — Number of inputs1 (default)

Number of inputs of the layer. This layer accepts a single input only.

Tips

In an image classification network, you can use a
globalMaxPooling3dLayer before the final fully connected layer to
reduce the size of the activations without sacrificing performance. The reduced size of
the activations means that the downstream fully connected layers will have fewer weights,
reducing the size of your network.

You can use a globalMaxPooling3dLayer towards the end of a
classification network instead of a fullyConnectedLayer. Since global pooling layers have no learnable parameters,
they can be less prone to overfitting and can reduce the size of the network. These
networks can also be more robust to spatial translations of input data. You can also
replace a fully connected layer with a globalAveragePooling3dLayer instead. Whether a
globalAveragPooling3dLayer or a
globalMaxPooling3dLayer is more appropriate depends on your data
set.

To use a global average pooling layer instead of a fully connected layer, the size of
the input to globalMaxPooling3dLayer must match the number of classes
in the classification problem

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